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This paper studies the last-column-block-augmented northwest-corner truncation (LC-block-augmented truncation, for short) of discrete-time block-monotone Markov chains under subgeometric drift conditions. The main result of this paper is to…

Probability · Mathematics 2016-11-23 Hiroyuki Masuyama

The Sobolev regularity of invariant measures for diffusion processes is proved on non-smooth metric measure spaces with synthetic lower Ricci curvature bounds. As an application, the symmetrizability of semigroups is characterized, and the…

Probability · Mathematics 2021-05-24 Kohei Suzuki

Strong invariance principles in Markov chain Monte Carlo are crucial to theoretically grounded output analysis. Using the wide-sense regenerative nature of the process, we obtain explicit bounds in the strong invariance converging rates for…

Computation · Statistics 2025-04-11 Arka Banerjee , Dootika Vats

We consider the convergence of a continuous-time Markov chain approximation X^h, h>0, to an R^d-valued Levy process X. The state space of X^h is an equidistant lattice and its Q-matrix is chosen to approximate the generator of X. In…

Probability · Mathematics 2014-07-02 Aleksandar Mijatović , Matija Vidmar , Saul Jacka

The switch chain is a well-known Markov chain for sampling directed graphs with a given degree sequence. While not ergodic in general, we show that it is ergodic for regular degree sequences. We then prove that the switch chain is rapidly…

Combinatorics · Mathematics 2011-10-17 Catherine Greenhill

We consider the problem of sampling a multimodal distribution with a Markov chain given a small number of samples from the stationary measure. Although mixing can be arbitrarily slow, we show that if the Markov chain has a $k$th order…

Machine Learning · Computer Science 2024-11-15 Frederic Koehler , Holden Lee , Thuy-Duong Vuong

Understanding the dimension dependency of computational complexity in high-dimensional sampling problem is a fundamental problem, both from a practical and theoretical perspective. Compared with samplers with unbiased stationary…

Machine Learning · Computer Science 2024-03-12 Xunpeng Huang , Hanze Dong , Difan Zou , Tong Zhang

We propose a new tamed Milstein-type scheme for stochastic differential equation with Markovian switching when drift coefficient is assumed to grow super-linearly. The strong rate of convergence is shown to be equal to $1.0$ under mild…

Probability · Mathematics 2019-09-18 Chaman Kumar , Tejinder Kumar

An elementary proof is provided of sharp bounds for the varentropy of random vectors with log-concave densities, as well as for deviations of the information content from its mean. These bounds significantly improve on the bounds obtained…

Probability · Mathematics 2019-03-06 Matthieu Fradelizi , Mokshay Madiman , Liyao Wang

We study inhomogeneous continuous-time weakly ergodic Markov chains with a finite state space. We introduce the notion of a Markov chain with the regular structure of an infinitesimal matrix and study the sharp upper bounds on the rate of…

Probability · Mathematics 2020-02-17 A. I. Zeifman , Y. A. Satin , K. M. Kiseleva

The law of the iterated logarithm (LIL) for the time-homogeneous Markov process with a unique invariant measure characterizes the almost sure maximum possible fluctuation of time averages around the ergodic limit. Whether a numerical…

Numerical Analysis · Mathematics 2025-11-10 Chuchu Chen , Xinyu Chen , Jialin Hong

We prove that in 1-D the growth of Sobolev norms for time-dependent linear Schr\"odinger equations is at most logarithmic in time for any (fixed) potential which is analytic (or Gevrey). Recently it was proven in [N] that almost surely the…

Spectral Theory · Mathematics 2008-09-30 W. -M. Wang

Langevin Monte Carlo (LMC) is an iterative algorithm used to generate samples from a distribution that is known only up to a normalizing constant. The nonasymptotic dependence of its mixing time on the dimension and target accuracy is…

Machine Learning · Statistics 2020-02-26 Niladri S. Chatterji , Jelena Diakonikolas , Michael I. Jordan , Peter L. Bartlett

A family $\{Q_{\beta}\}_{\beta \geq 0}$ of Markov chains is said to exhibit $\textit{metastable mixing}$ with $\textit{modes}$ $S_{\beta}^{(1)},\ldots,S_{\beta}^{(k)}$ if its spectral gap (or some other mixing property) is very close to the…

Probability · Mathematics 2021-07-01 Oren Mangoubi , Natesh S. Pillai , Aaron Smith

Contractive coupling rates have been recently introduced by Conforti as a tool to establish convex Sobolev inequalities (including modified log-Sobolev and Poincar\'{e} inequality) for some classes of Markov chains. In this work, we show…

Probability · Mathematics 2025-03-04 Francesco Pedrotti

We consider generalizations of Schuetzenberger's promotion operator on the set L of linear extensions of a finite poset of size n. This gives rise to a strongly connected graph on L. By assigning weights to the edges of the graph in two…

Combinatorics · Mathematics 2014-05-06 Arvind Ayyer , Steven Klee , Anne Schilling

In this paper, we prove modified logarithmic Sobolev inequalities for canonical ensembles with superquadratic single-site potential. These inequalities were introduced by Bobkov and Ledoux, and are closely related to concentration of…

Probability · Mathematics 2014-06-20 Max Fathi

We consider a stochastic conservation law on the line with solution-dependent diffusivity, a super-linear, sub-quadratic Hamiltonian, and smooth, spatially-homogeneous kick-type random forcing. We show that this Markov process admits a…

Probability · Mathematics 2023-08-29 Theodore D. Drivas , Alexander Dunlap , Cole Graham , Joonhyun La , Lenya Ryzhik

We prove the mixed-norm Sobolev estimates for solutions to both divergence and non-divergence form time-dependent Stokes systems with unbounded measurable coefficients having small mean oscillations with respect to the spatial variable in…

Analysis of PDEs · Mathematics 2018-05-15 H. Dong , T. Phan

We obtain several quantitative bounds on the mixing properties of the Hamiltonian Monte Carlo (HMC) algorithm for a strongly log-concave target distribution $\pi$ on $\mathbb{R}^{d}$, showing that HMC mixes quickly in this setting. One of…

Probability · Mathematics 2017-08-24 Oren Mangoubi , Aaron Smith